{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# ignore this\n",
    "%load_ext music21.ipython21"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# User's Guide, Chapter 55: Advanced Meter Topics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Objects for Organizing Hierarchical Partitions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Hierarchical metrical structures can be described as a type of fractional, space-preserving tree structure. With such a structure we partition and divide a single duration into one or more parts, where each part is a fraction of the whole. Each part can, in turn, be similarly divided. The objects for configuring this structure are the MeterTerminal and the MeterSequence objects.\n",
    "\n",
    "MeterTerminal and the MeterSequence objects are for advanced configuration. For basic data access about common meters, see the discussion of TimeSignature, below. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Creating and Editing MeterTerminal Objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "A MeterTerminal is a node of the metrical tree structure, defined as a duration expressed as a fraction of a whole note. Thus, 1/4 is 1 quarter length (QL) duration; 3/8 is 1.5 QL; 3/16 is 0.75 QL. For this model, denominators are limited to *n* = 2 :superscript:`x`, for *x* between 1 and 7 (e.g. 1/1 to 1/128).\n",
    "\n",
    "MeterTerminals can additionally store a weight, or a numerical value that can be interpreted in a variety of different ways.\n",
    "\n",
    "The following examples in the Python interpreter demonstrate creating a MeterTerminal and accessing the :meth:`numerator <music21.meter.MeterTerminal.numerator>` and :meth:`denominator <music21.meter.MeterTerminal.denominator>` attributes. The  :meth:`duration <music21.meter.MeterTerminal.duration>` attribute stores a :class:`~music21.duration.Duration` object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterTerminal 3/4>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from music21 import *\n",
    "mt = meter.MeterTerminal('3/4')\n",
    "mt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 4)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt.numerator, mt.denominator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt.duration.quarterLength"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "A MeterTerminal can be broken into an ordered sequence of MeterTerminal objects that sum to the same duration. This new object, to be discussed below, is the MeterSequence. A MeterTerminal can be broken into these duration-preserving components with the :meth:`~music21.meter.MeterTerminal.subdivide` method. An argument for subdivision can be given as a desired number of equal-valued components, a list of numerators assuming equal-denominators, or a list of string fraction representations. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {1/4+1/4+1/4}>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt.subdivide(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/8+3/8}>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " mt.subdivide([3,3]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {1/4+4/8}>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt.subdivide(['1/4','4/8']) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Creating and Editing MeterSequence Objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "A MeterSequence object is a sub-class of a MeterTerminal. Like a MeterTerminal, a MeterSequence has a :meth:`numerator <music21.meter.MeterSequence.numerator>`, a :meth:`denominator <music21.meter.MeterSequence.denominator>`, and a :meth:`duration <music21.meter.MeterTerminal.duration>` attribute. A MeterSequence, however, can be a hierarchical tree or sub-tree, containing an ordered sequence of MeterTerminal and/or MeterSequence objects.\n",
    "\n",
    "The ordered collection of MeterTerminal and/or MeterSequence objects can be accessed like Python lists. MeterSequence objects, like MeterTerminal objects, store a weight that by default is the sum of constituent weights. \n",
    "\n",
    "The :meth:`~music21.meter.MeterSequence.partition` and :meth:`~music21.meter.MeterTerminal.subdivide` methods can be used to configure the nested hierarchical structure. \n",
    "\n",
    "The :meth:`~music21.meter.MeterSequence.partition` method replaces existing MeterTerminal or MeterSequence objects in place with a new arrangement, specified as a desired number of equal-valued components, a list of numerators assuming equal-denominators, or a list of string fraction representations. \n",
    "\n",
    "The :meth:`~music21.meter.MeterTerminal.subdivide` method returns a new MeterSequence (leaving the source MeterSequence unchanged) with an arrangement of MeterTerminals as specified by an argument in the same form as for the :meth:`~music21.meter.MeterSequence.partition` method.\n",
    "\n",
    "Note that MeterTerminal objects cannot be partitioned in place. A common way to convert a MeterTerminal into a MeterSequence is to reassign the returned MeterSequence from the :meth:`~music21.meter.MeterTerminal.subdivide` method to the position occupied by the MeterTerminal.\n",
    "\n",
    "The following example creates and partitions a MeterSequence by re-assigning subdivisions to MeterTerminal objects. The use of Python list-like index access is also demonstrated. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/4}>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms = meter.MeterSequence('3/4')\n",
    "ms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/8+3/8}>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.partition([3,3]) \n",
    "ms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterTerminal 3/8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms[0] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/16+3/16}>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms[0] = ms[0].subdivide([3,3])\n",
    "ms[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {{3/16+3/16}+3/8}>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterTerminal 1/8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms[1] = ms[1].subdivide([1,1,1]) \n",
    "ms[1][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {1/8+1/8+1/8}>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {{3/16+3/16}+{1/8+1/8+1/8}}>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The resulting structure can be graphically displayed with the following diagram:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Ae3QFwbCFK7znL5v/xa8n3Gf/7i/hmwAC+M650SeopfxH1In8nxTkGgr3mQBo+mMuYz3d\nPYI41eHu2lWEU8/PRVSEU1JcQhz8B7RtRmlqECnVAAAACXBIWXMAAC4jAAAuIwF4pT92AABAAElE\nQVR4Ae2dB3wURRfAX3onlUAKvSNIRzpIR0HpRbrSxN4bFiwoxYZYQIqoWECKiNJBkA+kS1daQk0h\nIb2X+d6bvblckktIuSR3uTf55XZ3dur/zcybtrs2Ag2wYQJMgAkwASbABKyCgK1V5JIzyQSYABNg\nAkyACUgCrPi5IDABJsAEmAATsCICrPitSNicVSbABJgAE2ACrPi5DDABJsAEmAATsCICrPitSNic\nVSbABJgAE2ACrPi5DDABJsAEmAATsCICrPitSNicVSbABJgAE2ACrPi5DDABJsAEmAATsCICrPit\nSNicVSbABJgAE2ACrPi5DDABJsAEmAATsCICrPitSNicVSbABJgAE2ACrPi5DDABJsAEmAATsCIC\nrPitSNicVSbABJgAE2ACrPi5DDABJsAEmAATsCIC9qbKa3Z2tqmC4nCYABNgAkyACTCBPARsbU0z\nVjeJ4hdCgKkSlCeffMkEmAATYAJMgAmYkECpFT8pfRsbGzh37pz8d3BwALJjwwSYgHkSoPqakZEB\nNEvn5OTE9dU8xcSpYgKSgKqvNWvWhLZt25qEig0q6RJraaX0r169Ct27d4fQ0FCTJIoDYQJMgAkw\nASbABHITOHz4sFT+1GkvzSx7qRYMVJ/h1q1bUunXrVs3dyr5igkwAbMkEBgYCIFBgWaZNk4UE2AC\nuQk0atRIWtAg2xSm1FP9lAg7OzuZlsuXL8PIkSNh6NChcirRFAnkMJgAEzANAeqoOzs7w6FDh2DB\nggUy0ClTpkDfvn0hNTVVLtmZJiYOhQkwgdISUPV17969sGjRIhmcvb1JVDaYJBQ18qeUtWnTBkaN\nGlXaPLN/JsAEyoiAl5eXXvF36tQJRowYUUYxcbBMgAmUloAtDqyV4jfUtaUJ1ySK3zAB6enp8jIr\nK4tHEIZg+JwJVDABWhekEQON7pVJT0+Tp1xfFRE+MgHzIKDqa5pBfTVVykyu+GkHIhnaeKDOTZVY\nDocJMIHSEzDcFKTqKB0N7UsfC4fABJiAKQiURb0s1eY+U2SKw2ACTIAJMAEmwATKjwAr/vJjzTEx\nASbABJgAE6hwAqz4K1wEnAAmwASYABNgAuVHgBV/+bHmmJgAE2ACTIAJVDgBVvwVLgJOABNgAkyA\nCTCB8iPAir/8WHNMTIAJMAEmwAQqnAAr/goXASeACTABJsAEmED5EWDFX36sOSYmwASYABNgAhVO\ngBV/hYuAE8AEmAATYAJMoPwIsOIvP9YcExNgAkyACTCBCifAir/CRcAJYAJMgAkwASZQfgRY8Zcf\na46JCTABJsAEmECFE2DFX+Ei4AQwASbABJgAEyg/Aqz4y481x8QEmAATYAJMoMIJsOKvcBFwApgA\nE2ACTIAJlB8BVvzlx5pjYgJMgAkwASZQ4QRY8Ve4CDgBTIAJMAEmwATKjwAr/vJjzTExASbABJgA\nE6hwAqz4K1wEnAAmwASYABNgAuVHgBV/+bHmmJgAE2ACTIAJVDgBVvwVLgJOABNgAkyACTCB8iPA\nir/8WHNMTIAJMAEmwAQqnAAr/goXASeACTABJsAEmED5EWDFX36sOSYmwASYABNgAhVOwL7CU8AJ\nsCgC2dnZMr02NjZA/2yYABMwVwICsrOFTBzXV3OVUcWkixV/xXC32FhtbXMmiYQQrPwtVpKc8MpP\nwAZsbXM659QFyLmq/LnnHBZMIKcVL9gN37EwAqSQaWROR80IPM/W2ZUsM1pQAnZsXg+Ll62EmIRk\nqfRz4sgJV2DchvGr9KjZghyXfMYEmICqH4Z1yZhdsUllZ8CGNd/Dyh/WQHJqulT6+ibBILC8calr\nWYcN3PFp5SHAI/7KI0uZk2ys2bYG0/CyMdFdq5l5sivOND01ADTSP3/yMPS5b6iMJ8vBE2ZOGCw7\nF/qwMFw5qkC3amSRjR0OWxu8VpGjC2p8cq4rmQA4O0ygGARU3dLXB1WH8tRh/f0ihK3CPPzXDhgy\ncrz04bZlHwzv11kOAGywPiqj3KrwqdNuQ/VXX18hdx1XHvlo0QRY8Vu0+PInnpR+VPgNOHjoEJz7\n7wLExMSCwIru41sVWrVtC906dwIHO5viVWbZUAj45adV+gir+fvoz+WJps2lwg+9+B/sP3AArly7\nAQlJyeDs7ALVAwKhXfsO0OruptiocGOSGx5fWSMB6oBThzr29i04gvX19Ll/ISr6NmThuryXty80\nu7sl3Nu9G7g6OxSjvmphisxU+P6b5XqsVX2q6M+1E+qk01KALYRdC4X/7d8Pl0KuQHxCIjg4OoF/\ntWrQqk17aN+2FdhhhS3uYCFPZHxpbgRQoCU2WVlZ0u+xY8dooCf/3333XWmHPckSh8sei09A8d69\nZYNo06yeXh5KLur49MuzRXxyapFllK2Tceh//4hAnYw79hsuouKSc8JQss7KED+v+EpU99LKgorT\n8PjGnI9EQjHiLz4J9lEQAVVfN23apC8fixd/JZ2rewX5ZXvTElD19eiBPeLeTq318jCsK3Q+ftqT\nIuJ2vIxc+SksJUqO/xzcpQ9zyITHRHK61h6rVlkdt274STStG6B3mzf+J196Q0TGFD3+wtLG94pH\nQMnyxx9/1Mtnw4YNMhB1r3gh5rjOmfNBibOxTAK0fk9TczdDzkOf/oPh6OlLWkZcfGDwkKHQrGFN\neV2/Xl345IM3Yfn363QZpfJUuBE0PEezaf0vcFPndMrkieBbxUWu41O82Ihobn75DkZNngEZjtXl\ndddeA+D119+AMSMekNdBQYHw9qvPwvsffil7Bmo5QBcsH5iAVRDA5lfW18Tb4fDE+AGwe/8xfb4H\nPjAY2re+S17Xq18fvluyED7+ImfkrndYwAlN0wNkwdqfftC7mDxhLLg4YD2laXy0VccDOzdBv8Gj\n4VJ0hnTbon0XeHXW6/DwhDHyunpgECyc+za8+PocSM3Q2pg7txj6aPnEnAnk9AGKf6Z6HTziLz47\nU/pQI4Gom1dE/y5tRINmbcX8T74QZ/69IBISk8SVS/+Khwb1lr1GFxxFdB80TsQkpcskqMG6sfRk\nZ2szOuFXzosWwdoovlH7vuL6rVidX1zB1wUQHx0m+t/TWIC7n4xn6jOzRER0nHSXmpIgvvjoPWlf\np1awPB4/d1ney8J5TTblQ0DVVx7xlw/vgmJRdSYlPlo8PKy/8ApuKN56b744fvKMiItPFBE3r4qn\npoyR9SSgqrsIaN5DXI2IkcEpv8bCVvK9cPKwcNbNzvUaPEHEGdZ1XX3NTE0QU0YOkHGgfhIDR08T\nITciZLAZ6anixxVfynsN6teVxx3/OybvqTiMxc92piWgWPOI35x7UBWYNhp106DbN6AmfL/ud9iz\n4w94/qlHoWmj+uDq4gw16zaCcbpevHdVV7h5KwYSE1N0KaZ6bdwIoY3Jt/6+Hk5c19xMnzIJgvw8\nQW4CotkA3Wg/OioKjhz8F/wctNHDo1MfAX9cV8zMzAQnZ3cYM3Y8dGseBNFJaTKgkKthukgLjt94\nqtiWCVg2Aa2+CnD28IEPl3wPp/7+E9589Xlo2bwpuLu5gH9ADayv42Qms23dIOxCGCQmJMnrQmuL\nbnZuw9qfIFWHaPKkcVDF1UE3O6f1BuhW7O0ouPDvafCuWlW6fOqJR6F2oD9kYX21d3CC4aPGwEP3\nd4MLF8Pl/X8vXpFH/qkcBHhzX+WQo7ZhDvPiW7WazBEpZrJUz92npGhNQXpcMtTx9QQPdxz7S6Mp\nd92F/oB9V/RrAzGR12Dp119Ie7+6reGBAb01N7pGRm3ft7e3A2xfIN2Jwo0D7K1Kd9TIkaH+QUZm\nBjjZoyM0To7aUV7wDxOwMgJK+Xv5+IIX5R0rCNZYfX1NS9Xqq6NdNnjW9gN3D3dJyHhtRe9Y36mu\nX790BhbN/VC6bd19EPTp3knzp+qrvAKwt7cHBwfcNGiTKW2obpJR9ZW6CJlZeA87IiA36DrJ+/xT\nOQjwGn/lkKPMBTUKpLDpETpa68vCyhwZEQ4H/toFi5eskG6i0gEmjB4Onqiltb0BxgFQOGT+3PoH\n/HX8ijx/YuY0qBdcVedPa4JUQxEYXAsGjxkC4eHaCOGTTxfClRsRMj3xsbdhxdLFcOBcJNwKvwm+\nDTtBi6YNZJjKv7zgHyZgRQSU8qd6qPXcs+BWZCScOPo3fP75Ekni2s1b8NzUCVDDH2fZsE4WVF/U\nXpzNG9bCFd1wf+ojk8Hfy02/F4cC1OIE8KwaCL37D4TYSG3m7aOPPoFzOKqn/TrJifGwCp8IWL1l\nPzgnRaMvb+jQurlMj0yndsa/FkyAR/wWLDxjSaeKTX/0OM/nC96FZT9uhCv/nYJ4VPjgVQ2WfvY5\nTBo7BC+oETHe79NG+7aQFBsJK1cs1aJxrw1DH7xPntNjQDkjD+1RH1tHV3juzTlwGZX9pp37YdXS\nhfDP0YPQvXM7CPn3FGzesQdcXOzBJ7AxfLP0Mwjyx63/hTRkWqT8ywQqNwFNEVNtyoZVyxbBh4uW\nQ+TNqxAWFSczPv+zpfDYtEkahDyjds2SOvvauzKiblyGxZ9ro/2aLbrB/X3vlU7ydxaoU28Ljzz+\nPJy/HArLsY3Y8esP0P/MP3Af+om4dhnW/7YZl+icINXRD35auRLuqo+bfLC+0uPCbCyfACt+y5dh\n7hxg5aReeUpSPPy87D04pdvg7+rsDO5enmBnb4vr7llg52BXoOJVCvl/f26HX3cfkeE/8+xMaFa/\nBrUy+So/NSw0tV+zbmNYsnQ5jHtoOOw6FY5rkwfhi+MHpf/aNQMh9KoNrMRGpFfn1jgKycKpSbvc\naecrJmB1BHSjeOyob/t9DZw4eUoScHd3h8R0mo63w5k7XDZzxLqiq9t5ESnrbZt/haMh8fL2Y9Me\ngRrVvORoXy33KX9UX6n++VWvAZ9+9hUkJSXCzxt3QWZ8OHz1xefSWZ3aNSEk9Cr8vOZbGDmwJ8ZN\nu/qNDxRUuHy0HAIsScuRVdFSipWaGgJXz6qwYOk2WDB/PrzwzBPgapMKkaHnYfKYofD2/C/keqLR\nvjspdlwmSE+Og1XfrtTF6QBjhg2W5+rRPcPEUEfBzs4OIq6HwPtz3oMzlyMBEqPgdiJA127dgdR7\n6NWb4OOXAe+99x4cPHZGKn3coWwYDJ8zASskoNVXsMcZs9fmwUcfLoDXXn4B/Kvgmnp6LDw9YzI8\n/crbkFLA43RyFI71NT4qDJZ9vVjjF9AUBt/fTzvH9iCv0fzYQUJMJHzwwfuw9/BZ6eRm5G3o1KUr\nBOKmA1L6nt5+8NHcObB9L3beUenLJYm8gfG1ZRLAQlBiox434Mf5Soyw3Dxu3aC9BKJWzUCa5xMn\n/guRcWfleZ5PyXT/9l+lO3L7yFOviwxyncetDEBoj+NlpiWJZ6aO1Pu598Ex4sCRf0RUVJT47+xJ\n8fSjE/X3glr2FNcj7/x4khY+/5qKgJItP85nKqJlF87hv7YJR6x7tWvXkvVm98ETMjIlQxWzut74\n4zJ9/XptzmfytnocV7lVR60aZ4oP3nhG76dlp95i518HxK1bUQLfvCnefi3nHkCwOH3xmvSet71Q\nYfLR9ASUbPlxPsvsW5VbqqlHTqNo+sdiqDvXdtd3xJ78vW1qwc0Y7XG60Gvaph45PaBPoTbaz85I\nhp9+/FZvO3bMcKA1IWOjfWxEpLtLuI7/8derITg4GK99YO47s6FDmxbg6+sLDZs0hzfefBv63NMY\nHzkMhhv/7II9B45Kf5RONkzAGgnk1FGtvqr6Syxat+sADw3tAaGhNySa/y6GyqPhD/mn2bmUhOic\nvThQFUYMHSidqcdxc/uhKXuAsNALsOyTjyEgGJfv0Lz//hzo2aUD+Pn5Qq16DeGlV96AcQ/iEzyu\n9Gru67Bl517pzobrq+Rg6T881W/pEjRIP63BUUNA/7SOR//6ekr6FZU02kgfmUam2ZUSP3nsICxc\nvla6Gz7pSVTgzfEc/WK4BZn429HyVmzsdQhu0gpqBQdKP/Qcfyau/3v7V4cWrVpBdNh16e5WdJQ8\n5p+IlNb8wwQqPQGqn4b1FefTsZppH7qic61TrNWQDHq0Do1hfVGd5r//2glrtx2Q9x97+Wm4u1Ft\nGY7hJ3nlTfxR7UF8XAJcwO0A6Ym0ibAm1K9VUzrJyMjEx24zwdHNC5q3aAGQfFvaR0dFyCOlmY3l\nEyi4Jbf8vFlNDlQDcPbEEZg3dy5s/GMb3LodKxU/rb2TObBvD+w+fhUCfT3ktb+Ppzwa/kjFLjJh\nncHrPieOHwMu9rQZiDoNBRsnN+05Yx+fmnD93E44eoI2KdnI54XtMQ3XLp2H3ds3Q9VAbYRRxb2K\nDIzH+wUz5TuVk4Cqr1cunoUPF8yD1es2ws3wW7K+2mJdoXp29OB+WLl+D9SoFSQhBFX3l0d9fUEN\nTp0GfAMf/LDyG3mPfsaOGib9G5udo/tKbzvji7188dqlijf+XoX9R7TXBjs44IZCfMY/9tZ12Pvn\nboAq2gt+3N219kKlncJiY7kEaAaXjUUT0HYFC5yeXzD7ZVixfqfMTTd8T/79/ftCcFA1CLt6CT7G\nd25XxTeChYZegY79R8Jd+FY/MmqnLi0PUENy4fQxWPCJ9ghf76EToVuHNrncyQuDHzUCqNcQNxT1\naAUb/jwOAX4eMH3mE/D+W69By7saQPiNK/Dlwo/h6KVYCPCORd/B0LFtSy0U1RIZhMmnTKBSE5Bl\nXsDXCxfAe5+tkFltdU9XGPLAQKhbuwbE3LoJSxZ+BI6efhBzJRS8G3WEdi209/er+kaKnR6tO35w\nHyxdvVmGMe7Rl6Bti0Z4rnUKjDFU/mvUrgejxz0In3//K9SuEQDTZs6AlPj3oVO7FhAfHYHv3fgS\nft97DOrVDoBLODPQvUtHGRx1PAobABiLk+3MjwArfvOTSTFTpE3e2+BrNhs3x6k5VPzOrm6wd+dm\n+a8Co0/jpsZcw0t7+GD2LPB2d5Z7AEjZk9E6AALW//ITqJf5Pjwx53Wfyp10bPBDDQl1GlyxkZo9\n9xPYdU93fAY5ASDqCIwbNQSq+lfDl5Jo04TkLSwG4JvVS6BxnQCcdtSePzYIjk+ZQOUnQPPtWG/q\nN26qy6szKvC/5L/KvK0j1s/0VKDXb6z9eC4E+3sb1FdNsdO7On764VvlBSaMHQX4LR45O2dsml9z\nSEsIWO/ovRuz3sHP8e6Ffy5r+31mPDwWvPHz3THRt/RhXgoNgwVffAOdWzfRLR/wJLEejgWfsBQt\nWHj6pMuFOzuY+eyr8OWnc3F0oBoUvQtIdXCFSdMegyMnT0O39s3l+qFS5tQQ0CDkJj7ut+Lrr6Sn\n1j0GQ59uneS5GiXkhJb7jMKhKcC723eDI/gSkOeemA41AmgiEQyUvgsMGz0etu85ABNHDMA7NFPB\nxU9C4h+rJDD24Ufh++VfQp+e7fLln5T+8DET4M/9R2HogK54P2cUr/biXDh7Er5Y8pP0O3D0dOjc\nTptFK2wvDjmmekf1tU6j5vDbzoPw5ivPQsN62hq/odIf8MAwWLdpOzwzY6KMo/DFPumEfyyEAI/4\nLURQhSWTFDNVZHdPX5jx5Isw8qFJEHrlCkRHx8jev7OLKwQEBUFt3MDjiGt45NaYMqcdu5m3tfH+\nk49NAz8vV4NRRmEpoMZES0ODpi1g3seL4IlnX4CbN8IgOTUNX0LiCP7VqkGtWrXABd8GRo0YNSI8\nZVg4U75bOQnIuod1zcHZDcbiZ6wHDhkJV0JDITIqGl+ulY1vzHOG6gGBWF+pvtBDfdoMQX4aQv8x\nnhnTJoOrozb7pjr0+d3n2FAaqAMRXLsB4JcBYeqjT8L1GzcgMSkFX/LlgLv7q0Kt2rXAw81Veiqo\nzcgJkc8siQArfkuSViFpVYqXnPj4+ct/Y8610X3ukbYcAaDjgDqNYcPfhyAE5+N79eopvd9p9GAY\nh5YGnEa0s8dGo578N7xP52ovASv9vGT42qoI6DrKlGdPLx+4uyU9NpffqPpieEcp9obN28FhnKqP\nSsqG3t3bSyfqnqH7gs5pOUBT6LYQVKOW/M/rluKnNkB2VvLe5GuLJcCK32JFlz/hqnJSZaZ/Q6Pu\nFTS9rhTxXS3bwV26fXfkX9kbhlXYuQyf4kdHhmlQ8RenYSosHr7HBCydgKoThdXXQusLTtm37UjL\nACU3BaVB2Rcaf8mjZZ8VTIAVfwULoCyip0qrKm5xw6cZATmzSL384npW7il+PC9pGlQwfGQC1kCg\nNPWVRuRkSqugS5MGa5BRZcsjK/7KJtFS5odG7Ki32TABJmABBEqr8C0gi5zEMiCQe7G3DCLgIJkA\nE2ACTIAJMAHzIcCK33xkwSlhAkyACTABJlDmBFjxlzlijoAJMAEmwASYgPkQYMVvPrLglDABJsAE\nmAATKHMCrPjLHDFHwASYABNgAkzAfAiw4jcfWXBKmAATYAJMgAmUOQFW/GWOmCNgAkyACTABJmA+\nBFjxm48sOCVMgAkwASbABMqcACv+MkfMETABJsAEmAATMB8CrPjNRxacEibABJgAE2ACZU6AFX+Z\nI+YImAATYAJMgAmYDwFW/OYjC04JE2ACTIAJMIEyJ8CKv8wRcwRMgAkwASbABMyHACt+85EFp4QJ\nMAEmwASYQJkTYMVf5og5AibABJgAE2AC5kOAFb/5yIJTwgSYABNgAkygzAmw4i9zxBwBE2ACTIAJ\nMAHzIcCK33xkwSlhAkyACTABJlDmBFjxlzlijoAJMAEmwASYgPkQYMVvPrLglDABJsAEmAATKHMC\n9qaOQQghg8zOzgYbGxtTB8/hMQEmUEICVCdtbW1B4FEZVV/pSPfZMAEmYB4EZD3F+loW9dLkit/R\n0VFSs7OzMw96nAomwAQkAVL6ZJxdXOSRfhwdneQ511c9Ej5hAuZBQNVXZ2eTp8ckit9wZH/mzBn4\n448/ICMjg0f8JhdX+QdIvU0aDbJiKH/2po6RZOmCSv/AgQP6oI8dOwYBAQGQlpaK9ZVX/vRgCjnJ\nysqSbZvqSBXilG8ZEKB2hNhRW2KoMwyc8KkBAaqvzqj0Dx48qLc1FTcbFIY2N68PuugnlDAq/EeP\nHoW2bduCn58fREVFFT0AdskEmECFEHBy0kb6aWlpFRI/R8oEmEDRCQQFBcGNGzdg7dq1MHToUDn9\nX5qOp0lG/KXoOxQ95+yyQghUr15d9s7DwsIqJH6OlAmYGwGaIaE2Lzw83NySZtbpqVq1qhztp6Sk\nQFxcnFmntbInziSK3163nk+jfeqNDBo0EDIztemwyg6wMuaPGjXaq3H69GmYP3++zOKoUaNgwIAB\nvIRjwQJXcqXp/U8//VTmZMKECdCzZ0+W6x3kSuzs7e3lMuaaNWuk61deeQUaN24M6enpPHVdAD/F\nLTo6GubNmyc7S+3atYMpU6ZInnSfjXECqr7u378fFi9eLB1RGTSFMUkohqJr3749TJo02RRp4zAq\nmAAVOKX4O3fuDBMnTqzgFHH0piAQEFBdr/h79OjBci0G1JiYGFCKf8iQIUBKjM2dCURGRsKSJUuA\njvXq1YNp06bd2RO7kATc3Nz0it9UHSWTKH5D+dCmPjJqA4zhPT63DAK0d4N6lobrvzSqIcNytQwZ\nGktljlw1WZIblqsxUvntqMGlTWmqfSMXaamp0mFmZqbc65TfF9sobqnIisofmSzkRdP9tNFU2TGp\n/AQUO8N2GMA0j8ibXPGrXYe08UCd588S21gCAUP5qXOWqyVIrvA0KlmSK/WqDbIrzWahwmO0/Ltq\npJWbndYIEzdmZ1zGhtz07AzKGtnp7Y0HYbW2qlNUFmWLn9+x2mLFGWcCTIAJMAFrJMCK3xqlznlm\nAkyACTABqyXAit9qRc8ZZwJMgAkwAWskwIrfGqXOeWYCTIAJMAGrJcCK32pFzxlnAkyACTABayTA\nit8apc55ZgJMgAkwAaslwIrfakXPGWcCTIAJMAFrJMCK3xqlznlmAkyACTABqyXAit9qRc8ZZwJM\ngAkwAWskwIrfGqXOeWYCTIAJMAGrJcCK32pFzxlnAkyACTABayTAit8apc55ZgJMgAkwAaslwIrf\nakXPGWcCTIAJMAFrJMCK3xqlznlmAkyACTABqyXAit9qRc8ZZwJMgAkwAWskwIrfGqXOeWYCTIAJ\nMAGrJcCK32pFzxlnAkyACTABayTAit8apc55ZgJMgAkwAaslwIrfakXPGWcCTIAJMAFrJMCK3xql\nznlmAkyACTABqyXAit9qRc8ZZwJMgAkwAWskwIrfGqXOeWYCTIAJMAGrJcCK32pFzxlnAkyACTAB\nayTAit8apc55ZgJMgAkwAaslwIq/CKIXQnMk1EkR/LATMyeAslTiZLmat6yUfNTRvFNrPqkz5GV4\nbj4pNN+UKF50VO2E+aa2+CmzL74X8/ahBKZSaWNjo05LfKQgsrKzwc4W+0lUCooQJqWjdHHnLnCl\nC6vEWTcbj6aVqyZDKhnZ2QJsbfGsSHLVZFIqWWA8un6kZFuqsMxGOkYSosunKfJHYWRlZYGdnZ2R\niHJbmbac5A67vK5UHkrDTrU/QmRjsm1lW6TsCsqHipfulybugsIvD3stDzZFaaILTI7ilJ2dhW3D\nncscBWRp7CrNiJ8KuBIYFVr1T3aGQilQ2kZukC5AkcKa7xbDjMeegn8vXZVK31h4Kp5s7CCQKWnF\noXC0MHLyUNKwZEIs/KdguWryLkn2sEuGYs2E75Z8Co89/TxcunrzDnLNziWTEsWp5GpQNiubXGUd\nwPJPnSlqeUubP1XPDv21FSZNmgS7/ndYolf2hnKQcSNjitPwX2B6jLk39GsO55RGqvd0VOkvcbp0\nYaSnJMCHc96EV2bPgciYeBmuMRaKkYqXjmRUekqcjnLwSPlR7Cg6LQ8lj1jxjwoLheefnAGLvv4W\nUtKzZICGHXayyB+vVvYM7aVHM/ypFCN+lD0KXOvDpKWlQnp6hkTt4OAIzs5O8lwJtKgyoEJviyP8\n8ycPwcgJM6Q336AG8MGsJ/GcioBWOeiGYdhU8LKzMiEhMQlc3dzBwb54PUZV+bIyMyE1LU2OdKjX\n6ebuZhAjxVrJDVVo2Yjr5JqKcs3QydXRCZydHCUAQ/ZFIaLkevLQPpgw/WnpJaBOM3jjmckkSKmw\nVDg5YVOFxlmfzAxITEpGWXiAvV3R+swUBhkl10wMI03KFcsXjmDd3dxUdBZ8pFkMnaInmWFO0jGP\nVH49PKpIdsXNnGKfeDscXn16Ouw8dgWuJzvCPe3agpujTa4aqNxSHGn6cmIDjlhGnBxVOcnWtxHF\nTUtZuldpV+WD4kpJToJMHD94YJ0vicnGMmeLcvhzy0Z4Yda7Moi723SChwb1yNVWybJJ8qKZTDQp\nKcmQie2OjY0dtpvOYK9ru1QapSMz+jFMF/GjDkxCQgI4u7qBo0PpVNv3S7+Ejz9firldCh06doK2\nzepj+FjKaXYQDQ1ISOdQvNQupKSmAXF3sLcHFxcXaU/tidQU6MbcTOnomEluiOv5cyfhzz/3wJGj\nxyEqOkYKoYqnD7Tv1BmGDH4Qgqr5STuqEEUxWkdCwPrVP+mdt2rZTJ5TW24YDAk/KSEerl69AufO\nnYEjhw/D9u274fGX3oKJox7QFxJ9QHlODAvwlcvnYf/+A3D02DG4cTMcG890qZBaduwOzz75GHi4\nOOZq9PIEVTkudYBJUudOHUe5/glHj5+A6Jg42XB5evtBpy7dYPCDg6Can7e0IxkUxUi5igxY8+N3\neuetWjSW57KS6m01ZZ0QHwdXr4TA2bMo10Mo111/wUuzP4BRD/SRDY1qNA286U8N5Xrp/Dk4cOAA\nHDt+HG6GRUAadk6p8eh4b394cuY0cHEoWgdRH7i5nBjIKiY6CkJCLsOZ0yfh4IG/4cjpS/DRZ4ug\nU+u75OiROtJFNYrdnh2bpdInf13bt9aUPsap5K0a1svnz8CWLVvh2D+nICY2Dme3bcHXzx/atrsH\n+vXvB7WCqhernBQ1naVxp/IoRBZERkTApYsX4OSJf2DfX/sgOtUGvvric6gVWLV46UY2xDktKRa+\nWfa1lrwqNaBxvZq5kqrixsYFjh0+ANu2bYez/16QAxZ7BwcICAqGTp27Q98+vcDH0714acgVU9ld\nUBmgTtK1a1fhv3Nn4ciRI7Bzxw4Y+fAT8OS0CcVOs1LmNy6dhUUfzUMFbg/NOt0PQQH+MhOqidHY\n2UJ8zC3Yvm0b7MP2+sbNCMjIzAJ3Dw9o3LQZ9O7TD+5pc7fsBOewLjsWxQ4ZE1Vig+tu0u+xY8eo\n/sn/d999V9rhyKrE4RbVo4pj4+qV+vhVOgyPd3fsI86HXC9yurJ1+Qr974So6aHlq32vweJWXHKu\nMFT82zauEYMG9BV+Hra50vHMm3N07jVOxvKF60jSOis9WXy75DMR6KbFZ5h+Or9nwGgRFZ+iC89Y\nSKazU3LdvXu3Pj8ffvihLu7ykCtFlS1+XvmVPv68POi6U+8hIuR6RJHTpfL138m/hbuuvPZ6cLyI\nS07PFYZWdLPEb2u+FwP69BQeOrcqDbPmfqq515UTeZHnR5UhnG4VX3+2QODYzWhe+o2ZJuJTMrTw\n8oRh6kuV/02bNunTsnjxVzIada94cWplISM1UXy96EPRrUsnfbiK1TfrtxQ7fFWvkuOjxfD+HXRh\nVhPHzl7OFZZqYjavXZUvXhU/Hf3qtxA7/3dE+lX1rXj5xNKoi2zevHn6uPb99Veu9BQnTBVeTFSY\nmP3qc6Jdm1b6cFXa/z5xrtjhKznu3bpOH970594SWiujq7u6vGRnpIovP56jd6fiNTx2HzBM/Hvx\nikyHSnNJ8nn16lXRoEEDGdeIESNEampqqcPcv3uLGD54oKhR3S9XHsY99pzQ1ejiJFVkZWl8vv7k\nHX14i1aslmEorqr8hPx3Wgzqmb+8G7JbsGipSNc1/TryxUyP5vnHH3/Up2fDhl9zpadYARo4ttgR\nP+ZB9vpjwq/C1JETkbdm2nfuAV07tofIm5fhux9+gXoNGsLJA9th7sKv4auP3oKiZFhOMWNwv29c\nB1cTtHCnPTIZ/Kq45IxcdPFnpyXAZ++/BL8duCwdulfxgqp+PhBy+TK44pRPYUbLgy1kpyXBvLdn\nwStzPtE7f2TGk9CtU3vwr+oHHlWqQMPGTcHXw7nYvVh9gBZyonrd4VcuwqiJ2hILJb1Tjz7QGUd8\nN0L+gx/WbIAGDRvB/h3rYeGSTvDR7OeLlDttlChg47o1kKjz8cjkCVDFxUEvV1Wu0hJi4IPnxsH/\nrmoOq3j7gJ+PN1y+dAlccBq0MCPDwFFXelIcvPva8/DOpzRlqJnpTzwLXe5pi2XEF+XqCY2bNAUP\nZ3uLlKtiFXH9Ckx9/DmVRaharRq4Y9kPCQ3FqXYHvX1RT1S4B/ftgl+2/C29Pf7SE9CiSR1U49qI\nFpWQHNmePrQXBgwbC+BVDSA2Anr0ewDGjhwCWanx8O3yxbD/7E2IungCenUeDmcv7YMmdYOKNfNX\n1DQX153K44VTR+HNOR/qvQcGBoItzgBcD4vTT7Xrb97xRMcmPRl++G6l3vXY0cNxe1/ORlZUQnIp\nYOOa7+HRZ16FGrVqw7UroTBm4lQY0KcHRFy7BJ99Oh9SbDxhz+a18Mjj9rDx5xXgg+2fSrc+8Io4\nkUPvTFj59UL4ZcMfWgqcXKFWQDW4EhqCy2eucqRdnKRRvmiTb/TNEFi2+AvpNbBJJxjYr5c8p7ZD\ny7stJMdFw/OPPwy/7ToEgdX9IMXOE/cDzMTZGT/YuXUTrPh+DdSqGYRupoBf1eowceT9BF/OQhUn\nTWXqFjNTYqN6QRUy4tf1WtOT4sXsF58SA4eMEj+s3iDCIm7hWFEIGmm998pTsqcUVN1b+DXpIkJv\nRsu8FtZzVT268CsXRKs6PtJ/g/a9xfXI2Hx+1Yhj9+aNYtbrb4rf/tgsPnz7ZX3v7NU5apSs6/bl\nIa3SsXzRXOmndq0aAqpUE+v+2CnSM4z1EY3Z5QnUBJdKrhUx4ldMkuNui5efelQMGTlOrF63SUTc\n0mSXkhgrXnt6muRVzQtEww73iZtRCflkkxeDGoFfPX9a1PfRRt9tew4WkbFJ+fxqlLPF1l/XiNff\nmC3+2LwFy9Izerm+8/GXmp8CRvyqXHw+93Xpp2aNQOEZ1FD8vnOvyDRSFFSe86bZ1NdKrqYb8Wsp\nzEhNFquWfSnefX+e2Lp1q3hs8mg9q1WbdkhHKu475kkHLxPr75SR9+vD2Xf0bK5wFLN3X3pCuvHE\nLkGvQQ+JK+FaOSHHl84eF52b1RR+QbWkmzkLl8kwVFmQF0X8UfGZesQfFxUuPpn3vvj088Viy+8b\nxYDOd+vzfOT0eZm6orJT7o7t26EPY9TU50RqpkEmdXxTE26LUf07orbzlm4ffX62SNDNPJHrvds2\nSvt69evL44bt/ytWWlSMiltZjPj/3rtDvPbaLLHu101i8Sfv6/M89fnXRHHn0BS71cs/04czZ+Fy\nmQ1VXpSbfds2SDd169XBYxWxefffKrsiNSlOvPzEFHnfG8skzdTeTlCzG3pnRTpR8fGI37ALpOuB\nObh6wKvvzoW0DAFurtpIjDaoODi7w30DB8Br738KmeAIUZEJkIobMMiQVApaEcaOn1y/3775Vzge\nclu6nzFlMgRV9dSPCqUlhaELpEf/QUD/ZH6P1Q0R5VXBP7QRhdaHL545Ag8//hIE16oDoVdC4KeN\n22HIgJ7SI1Ya7GViTxE3kdDeBLWuWXColn9H9axdqnjD23M/goxsG5w50TZoklyd3Tzhvvv7wXuf\nLAEbJ1+IikmSm+UAcPK+EKNmcf74bS1c1MQKUx6ZCFU9XfPLVYZjA30fGI7/WqDxV88WEnrOLZIZ\nrbGeOboXHnvpHahdB+UaEgIbt/8F9/XsIh1KuepGAJVBrvZOLvDQwzmzM0d2/5YDpMCaZuDE4BQ7\nXbKsH8PNl0tX/y7vPDTjBWjXsgme06iMxq5U93AElpECkbci5DWu6sPIMWOgZjUfyMzAfTG4Qa1u\nk5YwbPQ4eHbWHOnm5o2bWt1XFVfaVsyPKudVfKvBUy+8LBMhcJZixadaWS9JquR+E9y/8vMPOaP9\nCWNHghNuH1HlUrV9CXGxcBPXxn187eD2LYCxD40Ed5x5Sk9PB3vcFN313l7wyPB+sOyXrTIpV66F\nlyRJZeKH2JG5p2sv+U/nB3doG3/pvLgGtbAsV/G3w2DFssWad5/GMGRQf3mu2g4sVPI6MjxMHi9f\nCoFhDz8NPXvcI0f06dg+OblWgdFjRsMHny0Fe38fOPHvNbgdkwDe7iRXRV96r9AfrRZVaBJKHrmq\nPPYOTlLp42hdBmaPOyvJ3Lh+Qx7TYyLg7ua1wccHxwVodPpanhv+qAIQe+s6LPtam+7xqtsWHujf\nW3NWQINB/nB9SLpRnQvDcI2dU2Ei88eGdfJ4HZU+NXAjB/WGLGy4kpKT5ZSknZ299v4A6co6fpRc\nHZycpdKnRouMXq7XNLnejoiGuxrVAC+vKjowxiVLnSdSsLeuX4KvFy+Ubuu1uhfu791DnquGRBeI\n/iDlqotbbrLU3yn4RG0K3bj2F+mIlP6MF96GQb27QEZ6GiSjXKn622EZle+FKDgoC7pDj1TpHuND\nxZORkVnCtOsUe1YarP7hW30YEx8aBY7YUuFgVW8nO+i4Cc3wqYhr167I+6S4tB3pmRB287rej6eX\np6z72l5rvXWFnahyrsp3UhLu5scNYiUxFAaV/n9PHoG5X2gbV/sPfwS63tNaBqeVy5yQnV1dwdPb\nC5KztE2l13VtpSM+BUEb1xOpYxB2A6pUDZCe/HRtZ04IFX+mtbsar5SU1BIniMIhs2/3Ntj8v9Py\n/JVnZkDj2gGyXOdsCNfc0dIrmWo+LnJDd0xsspzGJ3ZkwsNuyqNdVirUCfLGp4AKX/KVjsv5pyhL\n3uWcpOJFpxptEh499paUEAsXsScWcvFfmPuBtnYWgwP9Dx+danR0ZxgbhUHh7d2+Gf48elneevrR\nKVC/hr/cwa1GG4Z+6Jz86PS4fkSS143htUwrekiOjYRdO7bgLeoNpkHvrh1hx+aNsH7DbxCHj435\n4PpQL9wd2r9Pb3B2sNWtMRlXbobhV4ZzKVeUB1U14p4QexsuhYTCxX/PwAfzP5VZxHEdPI6zMV6u\nOWv0xvJO9Zrks3PzJjh6Plo6mTHtYQj299KPhIz5k3LV3ZAv+THmyMBOlZ/YWzdgGz5KBY44C5Ge\nCN06tIHNuF9kw2+/Q2JyKvhVD4S+/e6Dvr16gIOdWju0ZLkazEbpHnEywFLkU1LsxPns8cOwYPGP\n0t/9o6dD53taynND5aXtBbGHAQMfgDmfrZD33311NtSvFQT39e4GkJkOv639EeZ/kdOBuK+v1oFX\n5aHICStDh7Kc68Kncm54XZxoVYdzw88aN/L78MRxcv+IGu2THYVP5dTduxoMGTEWNj31KlnDG6+/\njrv3XaHt3U0gCdewl3/1mV4JutXrBF3aKxmYTzmV9VPX8BbUNsvMFfIj22Lknop7elZ9843OpQ+M\nGKZN9RmWFSWbVu07Q4dGXvD3f7EQgfuM5s7/CB6fPgl8PNzgzInD8Nbsd2Q44dHJ8NSIoVDdG3ds\nY8fYsPwWkqTyuYUZL7FRaxAVssafJ9VyXTYrXbw/62nSFQb/TmLVOm1nMVaAPL5yLtW9pNhbYkjP\ndpp/jzri5Pmr0hG+uS/HsZEztSN03TeL9HEXtMav1owun/tH+FJaXT2Er6+/6N61i96vYR6ee32u\nSNQt1N0hGUZSVnwrJdeKWOPPnVqNeTY+8TDrGW3dTM/FA/dCbP5TOlf7MnL71a6UXONuXRd92jWS\nfN3rtBLnr4RLB3eUqw74t59p+zAo/oLW+BW3c//8LeNxcvcU/tUCje52p3Bef3+hSNXt5ShPuZp6\njV9x1/KQKWY/P0Nfjldt2qlxLmA/hPJLR+X/nRdn6v2v3by3AP+6+pidKdZ897Vo2qC23k/7Tl1E\n25bNtWsnN3FXi7Zi7W+7tKhKCFqVI1Ot8WuJUUnS8pJ0O1wM79VGn4+irvGr9iT0339EdV3bd0/f\nYSIqz1NIKk6Vl5TkeDHvnVki0N9XH2e3nj1Fg1rV5TVukhPd+jwoDhw+Lb0qfyqcohyVH1Ou8RvG\nq+rcnk0/6/NQnDV+vf/NOU9BPPrSO9pTEEbKisrPqaMHxAN9uwkXN3cZb2CdRuLeHt31afDzry5m\nvb1AxCep9X1deTVM/B3OVdrKYo3foqf6sfHUGRyp45nIzoArIeeVpTzae7jC8WOH4eqNSH1vN5cD\n3QXKQJ7t37sd1u86LM+ffnoGNGtQgwKWU8XG/JXETosJ8JnZOKDxpyfuEk9NTYQ9+Pwume7de4Cf\nhzyFBvXrwYfvvAQrflyrWWBarMboQGXh6O3yBW0KTuXdw9kWjh45DDcibsuetJKfuq+Oyn7Pzs2w\n/fB/0vqZ6VOgQc1q2iyObsSg3JvimIijBzJu+PKopPjbsHfffrxyhh4oV20ngj3Ur1cH3nnlSVi1\nTlvHphGBNRtsUFGOAJfPnYBF87Rlti4DRsK9XdtLLGq0lcMIR660DINr+cMfGg8jh9wnb9WpVRMO\n7d8HR/B5/jp16+JEWhKMmjAFhg68V95XdS8nnMpwpo3CN25YDWolfio+reKrewopLzu6pmVRZxcP\nmDbjUejaoYWEEIhr0nt37YILV8KhTp1a8mVVjz7+OHRoexe2gTnvTqgMxLQ8aEtLmWmJsOr7b/TZ\nemjEEO0pCJ1O0N/AEyqjZN2sdQd4fOajkJKUCLSP5yY+bbQb3yPjVz1IOm/RoSfMnDkVPFyd5Ove\n88rAMMyKOK8kil83XWrvCq+8/TGsX7sWX16xBAbc2wkysRFe8O7rMPGxFyEmMdW48kdJ0lRRRko8\nfP/NCp0c7GD00Adlh8JgadGkMsrCN5uRccBHnpJwaj+wYUvYvHMvTvVvgF1/HoQh/brAhYuXwA+1\nxYeLlsDNKHztJqZTKTOTJsYcA8NaRnm1d/GEdz5cDut++QWWLfkSenZqAwm3wuC911+AmS+8CTgb\nopNr7kyQX5JrSnw0rFy+THezJgx7EB+vQaN1F3XWJjxkJKfI0BxwzS8J1x4btuoCO/buRrmuhz1/\n/wX9ujaTy1Fu6OrzJcshKj5ZptNq5GqMNbWoaDatXwvadj2AKQ9PAm83J7kck7fhJFZUF5JQts8/\nMR3e0nUWQq6EwZhxE2HU8MHykVqwc4Y3npsBL72Fj6elU+eCypSxBFimnZxCxuWRiKsX4KvP5shM\nNGzTCwb06i7P83IjS61e2MF1HCSNHTUMft64S7rNdvWDyY9Mgfv69MAXMV0Bd09PGPNgH1i8Ever\nKI0nXVaOHxzQy4ycwBcYLVmFS3Noxk5/Adq3xI4OtQ5YvvIaIbRl3dUrF0PfwWPAw81Fbt7tM+AB\neATLq4dtkvSyc+MPMGzkODgfckPu5cHxft6gKvYaC0GJjZqKqOipfjX9kjcjF08fEbXx0dPadesS\ndbFl72HpRKVbuVfXB3b8Jt2R28lPvCbS5exM0aZoijPVr+I7fmCnjK9GzVry+N1abUlCpevU4T3S\nPiAgQB73HT1jNP3KvamOKn0VPdVfkFxPH90nX6pTVyfXPYdPGeWi8rHrt9WSH8n1yVff103jGXmu\nzghAtRRQnKn+v3dpj0LVrKXJdd2WPblCPrx3iybX6tqU6tEzF3XpL1pZyxVYMS4UD3Ob6ldLNTcv\nnxNNcT8VyalZpwEiLLrgxzSVXJYtfE+693YF0aj9veKvQ8cFvipY4BvdxK4tG0QNfOTTz7+qdPPN\nmj90nIsme0O0qiya21S/ane+XZTzYqGPFv9QSD61MkbLZ089PExyId6Dx08X+C0Sgbv6RUJcjPju\n60/lPT8vB3ncdyz345SGbAo7V9zMcapfkshMEy/NGK/nsGWPcR1BeVT158zRv6R7pyraEsmX364W\ncfGJAl9TLS79d0pMGH6fPryRU54TKXI5r/h1W8XHU/1YQvMalId+FI+FTI4OcM0Ld8QD1K7fEHrh\nLvnQy5elt9Br2m7L3GFoo0J6NOhHg53E48YMAwcchKheYW4/ua8oDfRPRh0Nzw3vk702tgFwddd2\nhybjdBGAP7RqTo8s4b4kfCyETJ16DeH+DvUhLFybOk5I1EaS8mYl/yFm2ugMP16C5yRbrAhSK9Rv\n2AQG9G8Lly9rY8NrN9QY0QAK+tHP4nyrRvuAI8EHddN4Bm4LODWUm7Gd4GRnKG8VjBs+ikgmIQEf\nMvNqCs0aN5TXSq71MP1dGvlBZHystE9MUnLVypC0tLAfPSvknisXeE1Gf99IvmgURWbL7xvgbJjm\nYNrUyVDdx93oaB8Dk0tvqQlRsPlXHI16+EEMbqx+5fkXoUu7lvKlQc4urnBvvwdh1qzZ+CjvLS18\nfJ0rDvqxXKgaqMVVob/Ey5CRAT1FUrIzkkiyp7zERl6FpV8vki5s67SCB+7XNjHKUXoefyqua6EX\n4aflayE4OFi6ePGZZ6BR3RryaQh6Cdk4fDzz8UnDISpWe0zuz73/k+7MiFyuMqXyJRMpmRZe5qg9\nobycO3kY5n6lPQVx3+hp0Em/iTH/aF/x3Ld7p4wmDWebxk57DqaOHwFVcGMfveq4bsNm8OJLL8v7\nQfgyptVLf4LLV+kpJFxe0clZ3qzgHyO5q+AUFTN6Ug4Z+OwpHamhp3/6kALV7Uy0vx2Nq+j4ZiUy\ntkY+rKIU+6njB2Hh8jXS3eDxj0PHttq6l7HpHunI4IfittOFbY8fXlGGPsJChp42IDdYFOW1KkDV\n/KvBvS1rQ3QKVa5IiMMP+5BR672kKBLwGwCA7+cn4+zkII/W8EO86JliKVclWzwSxQz8ENNtfC+8\nUxVnicIWd8bnNaqS0fPgy9dslbcnzHwZ2rWgzpXWKcjrJ++1lKtuuk89Skhu8slVV6GliPF+tWoB\n0LqOGyRnoJaJvSHXSsmfXJPGo5RrfBQ42mlyLcnb7Sg8czJSTlTpbOgxxZw6oLjRJ3XJTa4GGjOg\nlNft8Cuw9CtNeVVr0hEG9esps0d+8hrVsUjDZZT4qAhwlYNSgKr4lksy9Dhhhq7zXC0At7vpTDJ9\nwEc+dovpUJYVfcT8UZtFxhEVh63uY2N0nYsdWeQxiuXu7X/A3hNX5d3XZ06HekH4fn9UbDmPoeV4\nVLonBZ8uoe5ySjINOqqDj5e2qSgT+WRiBxtsHfF9/dp6NflOTtJeYWpMHnS/IgylRX2qWbGidFD9\npEEb7aIvKL3aDvtsWLfmB33SJ49/SP8UhJFih22PVhZxdK/3U71aVaDSnoUfZqMPq5Hx8vUD6vrH\n4xIePtyH7xlJJWtqdszGWKziV4X+2IHd8PDDk+D9+Z/AP6fOypf0UOEWuHlly6ZfYf3O41CnppcE\nXrtGYD7wsgDgs8frfjIoABPG4EdT8FW6ul5hPk95LGJjouEGvhwkLjYGYuJwlKczSYmJcOt2LD5L\nfBNi46niYMHBxFFhpDR6+gdD3/sfxFqFyh3Njz+vAZwWAvqqIJm9u7bD3jOREOzpBBB0NwQHVpP2\nBRVmedPCf5RcD/y5BSZPmgjzP/kcTp39T36sCMnJLx/+vnED7DgcCgH4mAyZmoE5jbuWfZ1iz0yF\n1d9/p1nh7/gxIwDFWqRZHPIUczsKbpLsYm5DbJwmI7JPjI+H6Fh8zhnvxSVgZ41aCSlX3H+B96sG\n1YL7HhwNadRpgzhYvXYdvoiI9nJoct29bTOcwJGtF4o1oHkXfO2nPwVbYCMlb5rxD3VUb0VG4MxU\nBERHhuOm1ZyGkepGHNYJenlOckqaruzntIBK3ru3/g77z9DICOAJ3HxZO8BXKi9jZV1rfmnGzAP8\na9WH5NvUwAKsWbcW8LsHWH8c5FfS4m9HwPr1G+Q9+vHH1y5TvaYWWIWhv1lBJ/SyofCwMHwRURSE\nRUZCim7fDyUnKipKlr2wsHD5ARjDJBI36jAkxd0y2L9SG0YMGSidFZRDpdA8qnhAPRfsbOALsUg5\n/fqH1jmmr8vR4CXk35Owfs3PWJZryvB8/bQ6puRlmJaKOo/Hdw3cuHFDlq+o2zH6ZCTjACosMkpy\nvU0fbMpjqFNEHEIxj5+//4W822XAKNxIeo88N1bm6IbKu7+/1sGsiR9Q+gH3k534LwQ7IMgNyx2Z\nbX9sAkqNZxWs71Wb4FcWtU6VYi8dVfQPZqbERq1BVMQav7ZikiWenDycWhH9P27sEbPeeEPMmDpJ\n2lUPqimPXe57CF+dqD5yo/Ote8To/KmDAou/dHfvA+NFbJL6aEvBaLJ0H9c5dWSf6N6pjbinQ0fR\npXNn0bhhPeHl6Sn/69SrLzp36SLuaddG3DtgiDh7UXs0EDsU+vWif/85IOP1rR4sj1PwAxObt24X\nX346X2CvUQTXptdCgnh1zkL5KmK1Hlpwykp/R8m1wtb4M1PFI8P7yHxrsnUR4yY+gq/PfVNMmayt\nxwXVrC3v3zd6hv5Vo4hVGpX+U4f+1IcxaNyjIjFNW9tV7oyRUnyP7NsuOrRpLjp27CQ6o1wb1q+L\nMvUSnijbuvUbSLm2a9taDBgyWly8GiaDMpTrP3/vknFXD64lj489+4rYum27+HT+u/K6Vh1t30lp\nXiNrLP2F2Skuplrjp/yS2fjzSiz3GpNOHTuIOrWChZe3j/D08haN72omunbtKlre3UxMmvmCiI5T\nr0jG7oLOP356V9zX+S5NVtWaiDOXb8hw1Tq+vMjzo9a21377pfSnXi07ZvJM8evG38WGtWvEmMED\ntHt1tLr1244DWrhFeLQwT3T6tJp0jT8rTSyc+4Zo2KiJ6ELtRPt2IqCan/Dx8UV+3qJF6zaSXZPG\njcR7Hy8WmYRbx0zJctuGVRo3bCOeeWOelmxdK0qNoAAADg5JREFU25Q3D+paBpGdId55+THpt35d\nrS49/+pbYsvWbWLVymWic1vtcciq8iNlAeLUhWvSe2EyUeEbHpWMTbXGr+pnyH8nxcA+3UXb9u2x\nLnYWdzVtJLy8PIW3l5eogW1mx06dRacO7UW7rr3FwRP/amnXyV3lYeGcV/Tslv+8KZcbwzyoc8PH\nJt1JX1TR9o40bd1ZLF/5g9i6ZbN489XnZZi169aTx2den1fgo4Eq3IKOSsZlscZPvZgSG5WwClH8\nqtH5aYVeeIYdgFznwa3EweO5hU+Z1oLIFgtma8IiP9+v3yZ5qLwVBEfdX7dC2wSTKz4qFEb+N2zf\nlytsVSl+W114HoZNnCkiYgre6FRQGktqr/JWEYpfMfl5xRdGGRpyDW7WVfxzNkTHVKf18UqeZaeL\n2S9M14exfmvRvqSmFMrKT9/W+zWM09j5jn3al98UN13RFKu/+bzQMMY/+ly+zmhJZVYUfyp9plP8\nWqwvTh9baD4NmZ25pH0lkxpflZ4/flmp9//i2x/LQFUDX1C+VDnJSEsW7xh8R8EwLsPzOZ8sE+qV\n9TklpaDQ89ur+Eyi+HUFJC0hWvRqarytMEw7ndfrOFDEJuveQK/zn5oYIyYM7a1nd+jkBZlwxTV/\nLjQblZfbEdfEpBE530PIG6e6/uX3XdLjnWRiLD4Vl6kUv8rbnt9znttX6SzouOSH32TSyK/Kw40Q\n3Eha006ya9qhr7hxK06Xx8JLh+o07Ni0Rs+9oHgHjnzY6DdejHEyZqfyWhaK3x4TbZFGTZsMGjke\n/sI33P28dj3sx2+A37wRBun42kv68llwzdr45ru+MH78BHyjV6CcqlHraQhaTjtG3QyFn1Z+Jhk0\n73w/9OnRWZ4XNN2jYKn7nXoNhHfewCnOhBQ5RYYlS9Zk5Y7iy8zIgKqBtaFj6+a5wqbpRio9A0dM\ngv17gmHZ8hVwFJ8/TsDNXi7O+LWpOvVg4IND4KHRuHnErfJ/mY/gqCnYEROmgl9AMPyybgMc+PsQ\nvj40HNfRBHh4egH26PHNdwNg/Lhx+J11fKsiTjXnyJWm8WzhZugl+ParxRQkdO43Cnp0bi/Pldzk\nhZEfVa56DhwJb4YnQXxahvY4Dso1x9C6rLa3JLBOQ9yU2VjeUmFrK8g2MGLiTPgTp/2Xf/MtnDh5\nFhJxTdrV1Q3q1G0ADwwZDqPxK3Juzo6yXCq/OXFYwhmVXhsY/8hjkO3iB8LOAdnTRkyy1wzli/5x\nxzM0a9sZ6tUIkDdIznL/DC7HbPp1nc61Iz6Pr96Ypj02pbuR70BhUh22d3SB196ZC+06doaf1uC0\n6+mzEBONE624z8DXzw9atG4Lo8aMlfVa1jdMmpJxvkDLy4LSjnE5uvvAq/PWQdMtu8AJ3+VB+aF/\nZRS7NGTXd9Aw8MTvwys3dO/CuZPw7bod0vnkJ2ZB6+b18fzO+1cUO29cavx82XfQa8BqWP/r73Dh\n0kWIjU0AR2cXqIr7jzp26Q5jx46FNvg2P4xY1iuVtoo6UtrJ3N2uKyyY8zZci7wtl3WoDTBAJ9sD\nWnN39/aHfj06SD8q3xTEoX274exV3MuAZurDkyHQr4pc2lXtiLxh5If2TVA8ve7Hrz2eOAKrVq2C\nPfsOQARuIE1JSwdPbJ/q1GsAAx8YAqNGDAMvD/qiK8lES7eRICvEymIVv6YiqBbbQZee/aEzfrY1\nIiICN1QkyBcm0HoqTjfKT6kSWex56pWDIWlnFzdsHHrCkcub4aXnnwR/r/wfbTF0r85lIcKLajXq\nwqzZ7ynrOx6p4qrCSy0QNQG0HtexW29o37EbhGMe6L3w9L5xnPLD9SFXGWYuf3eMxYIdUK0kRrb2\n0LMffvyod3+UayRuckyUcnV0dAJv5OLjjYszaPLLVatgLm4e0LZLN7i0eS889+xj4OXmaMRtfk5K\nrsF1G8Fbcz7I76AAG2oMDOUqWwfMS/fe90Onbr1kHtLScf0Zy6Wvrx9+WwIXWNFYslxVfpu16wjz\n8b84RnG2wc5C/QaoWOBXeBk/ttWqWV0p/6I0lDIMKisYRj9UjL36DcS18lv4PQR8SgLZu7q5gz8q\nMHvd5k9zYq3UQM/7hwD9F9VI5lTY0FTx9IG2dX2x7UqD6Y+Mk5vMiqpkNHbZ+NJQbxg3eToMHTkW\nonEjNH1rxBbXq+l99PRJcDJmxQ3lSunxwm8IPPfK6zJ9RflReaAjGX/di3aadRsEwx/sL+0kW3lW\n+I/WRAlocncbeBf/o25FSr1DGyOpA+fr6ys/DUyhUHxFKcuFx2j6uxas+AmGVn20xt8OqgcE4n9u\nSASeRJ23J6caDeoRzv9yBTzxRhQ0bdpUes7rNneIOVcUuypIdyo0BbvT9opSHuxQ2QcF18iJAM/I\nnsK+U/i5PFn6BdUslJpsxLBRDwgMgjxi1XPPKyslV2//IFi04kd47VYcNLmLFEv+MiAtjfyYRK4y\nD5r8HBydIbiGtklKRVeZ5Fpw2Va51Y7kLlc5pkYYO+4zn3sNeg4aBXUaNJKPWlJ91Wp2bv/GrmR4\nGA5O0OLo3wkCg7TH0wzdau1DwTu8Dd2W93k+JgUkwNAdzZQQupoNmuFbRg9BQlo2NGmIo320zFsf\nCghOWtPMGIVL/9RJov/cRlcHMT5zMqqOU5pylScjiaS8GbpTfDr1Hgj/nTuDsy7e8psdhnyNBJPP\niuKVdRjZ+FX1l/+Gjsy9flu44tdQK2GqQqwEQMKR/8oiz5HukR9vv2ryn24Xp9Eh9xRGUcyd3Gl5\n0CqhrqzKsFXeihJH5XKjTadTngqSa0H5VXL1qxYI9F8Scyd5qTDv5E4vV5zu05ogrcxUJrneiUFB\nrJScnFzdoUVL7SMwxW2AZdhYB7VH1/LXH4rDnFmXnJ1WL4Jr4QwJGWo0itgWaR60X4pfyYHYK6Ps\nzXG0SmksKTeVPxwGQMPG2kCvRGUOA1Llylj7pO7lxGdeZ5VC8SukqrCq66IcDQs9CatoarwoIZfE\nja6jUrGJKEnCy9SPKeRapgm8Y+AoV1zjY7HmB2VY/0oi59whWlf9kexwRpDUdWkVTenZ55aEJVzR\nqJw6S8bed1Cc9Fsiu0ql+IsjLEO3lig4w/TzuXECLFfjXMzNluVUconQtD93KEvGr7SdpZLFah6+\nzGvxxjyYcCqYABNgAkyACVRaAqz4K61oOWNMgAkwASbABPITYMWfnwnbMAEmwASYABOotARY8Vda\n0XLGmAATYAJMgAnkJ8CKPz8TtmECTIAJMAEmUGkJsOKvtKLljDEBJsAEmAATyE+AFX9+JmzDBJgA\nE2ACTKDSEmDFX2lFyxljAkyACTABJpCfACv+/EzYhgkwASbABJhApSXAir/SipYzxgSYABNgAkwg\nPwFW/PmZsA0TYAJMgAkwgUpLgBV/pRUtZ4wJMAEmwASYQH4CrPjzM2EbJsAEmAATYAKVlgAr/kor\nWs4YE2ACTIAJMIH8BFjx52fCNkyACTABJsAEKi0BVvyVVrScMSbABJgAE2AC+Qmw4s/PhG2YABNg\nAkyACVRaAqz4K61oOWNMgAkwASbABPITYMWfnwnbMAEmwASYABOotARY8Vda0XLGmAATYAJMgAnk\nJ2Cf36p0NkIIGUB2djbY2NiULjD2XSEESHa2trZAR2VYroqE5R7vJFfLzVnZp5zKv52dHah6QDFm\nG7R1ZZ8Cy4xBcaOyl4ud7prsDO0tM5dlk2pj9dVUMZlc8Ts4OMi0USVhY5kESOmTcXZ21meA5apH\nYbEnxuXqKPNjb2/ypsBiORWWcFUPyI2qH8yuMGLaPRcXFzmYoCvSDXRNhgeHEoPRH1VfnZycjN4v\njaVJaruh8EJCQuDgwYOQmZkJcrzPo/7SyKdC/FJPkxq148eP6+O/ePEiHDp0CDIyMqSdocz1jvjE\nfAngyIpGqCTXEydP6tN5/vx5OHz4MKSlpekbZv1NPpEE1IiUlP6lS5f0VI4dOyYVV2pqKrPTU8l9\nQuyoYxQWFgbJycnyZmRkJOzZswccHR3lrCK3JbmZySuD+nrmzBm9A1OpUxsUjDY3rw+66CdqKuLo\n0aPQtm1bqF27NkREREBKSkrRA2GXZk2gevXqMn3h4eFmnU5OXPEIsFyLx0u5JiXm5+cnL7lOKCpF\nO/r7+8sOEnUyY2JiiuaJXUkCDRo0gAsXLsC6detgyJAhssOkZgRKgsgkI34PDw8Zd2hoaEnSwH7M\nmAA3bmYsnFIkjeVaMng0k8nsSsaORvpsSkaAlD4ZHx+fkgWQx1epRvwUFk0Y0FTNrl274MiRI0Dr\nEaWYRMiTPL6saAJqUw7v2ahoSZg2fpZryXlmZWXJNq80I66Sx265PkkvZCM7O95PUiwhkn5NT0+H\nevXqwaBBg8Bwn0mxAjJwXGrFbxAWnzIBJsAEmAATYAJmTsAkU/2URxpB8CYNM5c2J48JMAEmwAQs\nkgDNmJhqlolH/BZZBDjRTIAJMAEmwARKRoDf3FcybuyLCTABJsAEmIBFEmDFb5Fi40QzASbABJgA\nEygZAVb8JePGvpgAE2ACTIAJWCQBVvwWKTZONBNgAkyACTCBkhFgxV8ybuyLCTABJsAEmIBFEmDF\nb5Fi40QzASbABJgAEygZAVb8JePGvpgAE2ACTIAJWCQBVvwWKTZONBNgAkyACTCBkhFgxV8ybuyL\nCTABJsAEmIBFEmDFb5Fi40QzASbABJgAEygZAVb8JePGvpgAE2ACTIAJWCQBVvwWKTZONBNgAkyA\nCTCBkhFgxV8ybuyLCTABJsAEmIBFEmDFb5Fi40QzASbABJgAEygZgf8DsmqXXT5SNM4AAAAASUVO\nRK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3/8 divisions\n",
    "from IPython.display import Image #_DOCS_HIDE \n",
    "Image(filename='images/usersGuide/advancedMeter-02.png') #_DOCS_HIDE "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Numerous MeterSequence attributes provide convenient ways to access information about, or new objects from, the nested tree structure. The :meth:`depth <music21.meter.MeterSequence.depth>` attribute returns the depth count at any node within the tree structure; the :meth:`flat <music21.meter.MeterSequence.flat>` property returns a new, flat MeterSequence constructed from all the lowest-level MeterTerminal objects (all leaf nodes). \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms[0].depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/16+3/16+1/8+1/8+1/8}>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.flat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Numerous methods provide ways to access levels (slices) of the hierarchical structure, or all nodes found at a desired hierarchical level. As all components preserve the duration of their container, all levels have the same total duration. The :meth:`~music21.meter.MeterSequence.getLevel` method returns, for a given depth, a new, flat MeterSequence. The :meth:`~music21.meter.MeterSequence.getLevelSpan` method returns, for a given depth, the time span of each node as a list of start and end values. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/8+3/8}>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.getLevel(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/16+3/16+1/8+1/8+1/8}>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.getLevel(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0.75), (0.75, 1.5), (1.5, 2.0), (2.0, 2.5), (2.5, 3.0)]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.getLevelSpan(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0.5), (0.5, 1.0), (1.0, 1.5)]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms[1].getLevelSpan(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Finally, numerous methods provide ways to find and access the \n",
    "relevant nodes (the MeterTerminal or MeterSequence objects) active \n",
    "given a quarter length position into the tree structure. \n",
    "The :meth:`~music21.meter.MeterSequence.offsetToIndex` method returns, \n",
    "for a given QL, the index of the active node. \n",
    "The :meth:`~music21.meter.MeterSequence.offsetToSpan` method returns, \n",
    "for a given QL, the span of the active node. \n",
    "The :meth:`~music21.meter.MeterSequence.offsetToDepth` method returns, \n",
    "for a given QL, the maximum depth at this position. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.offsetToIndex(2.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.5, 3.0)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.offsetToSpan(2.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms.offsetToDepth(.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " ms[0].offsetToDepth(.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 0.75)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " ms.getLevel(1).offsetToSpan(.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Advanced Time Signature Configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The music21 :class:`~music21.meter.TimeSignature` object contains four parallel MeterSequence objects, each assigned to the attributes :meth:`displaySequence <music21.meter.TimeSignature.displaySequence>`, :meth:`beatSequence <music21.meter.TimeSignature.beatSequence>`, :meth:`beamSequence <music21.meter.TimeSignature.beamSequence>`, :meth:`accentSequence <music21.meter.TimeSignature.accentSequence>`. The following displays a graphical realization of these four MeterSequence objects. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Ae3QFwbCFK7znL5v/xa8n3Gf/7i/hmwAC+M650SeopfxH1In8nxTkGgr3mQBo+mMuYz3d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lEsU6KTuJCtxsb29dYBrrU6ZVEcMT3PAg8kee0DbajBXEyQfDpYI4KBYgJziGUj48j8+yHmX9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\n+c1P56B0S+FxMLEbxv1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795lJ09D/XBL88ssb0ptvv5uOWJp/gixP1hPzq2vy9xhS9+RA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\nJRB4MjHTeRtem8cckBtWOb+bbjdevm5qMy5fdaY99avyfFPOsaWTMzcuGx9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NvuF4tuA3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\nLRUDH+OZMYcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 29,
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# four MeterSequence objects\n",
    "Image(filename='images/usersGuide/overviewMeters-01.png', width=500) #_DOCS_HIDE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The TimeSignature provides a model of all common hierarchical structures contained within a bar. Common meters are initialized with expected defaults; however, full MeterSequence customization is available.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Configuring Display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The TimeSignature :meth:`displaySequence <music21.meter.TimeSignature.displaySequence>` MeterSequence employs the highest-level partitions to configure the displayed time signature symbol. If more than one partition is given, those partitions will be interpreted as additive meter components. If partitions have a common denominator, a summed numerator (over a single denominator) can be displayed by setting the TimeSignature :meth:`summedNumerator <music21.meter.TimeSignature.summedNumerator>` attribute to True. Lower-level subdivisions of the TimeSignature MeterSequence are not employed.\n",
    "\n",
    "Note that a new MeterSequence instance can be assigned to the :meth:`displaySequence <music21.meter.TimeSignature.displaySequence>` attribute with a duration and/or partitioning completely independent from the :meth:`beatSequence <music21.meter.TimeSignature.beatSequence>`, :meth:`beamSequence <music21.meter.TimeSignature.beamSequence>`, and :meth:`accentSequence <music21.meter.TimeSignature.accentSequence>` MeterSequences.\n",
    "\n",
    "The following example demonstrates setting the display MeterSequence for a TimeSignature.  NOTE that there is currently a bug in the first one that is showing 5/16 instead of 5/8. We hope to fix this soon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TRq/34Tf/WZpF+Jl6qW15TSTkwI1FB6JC9QJ3FR2ECvUC/QuKq5wew8XVpayd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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 49,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from music21 import stream, note\n",
    "ts1 = meter.TimeSignature('5/8') # assumes two partitions\n",
    "ts1.displaySequence.partition(['3/16', '1/8', '5/16'])\n",
    "ts2 = meter.TimeSignature('5/8') # assumes two partitions\n",
    "ts2.displaySequence.partition(['2/8', '3/8'])\n",
    "ts2.summedNumerator = True\n",
    "s = stream.Stream()\n",
    "for ts in [ts1, ts2]:\n",
    "    m = stream.Measure()\n",
    "    m.timeSignature = ts\n",
    "    n = note.Note('b')\n",
    "    n.quarterLength = 0.5\n",
    "    m.repeatAppend(n, 5)\n",
    "    s.append(m)\n",
    "\n",
    "s.show()  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Configuring Beam"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The TimeSignature :meth:`beamSequence <music21.meter.TimeSignature.beamSequence>` MeterSequence employs the complete hierarchical structure to configure the single or multi-level beaming of a bar. The outer-most partitions can specify one or more top-level partitions. Lower-level partitions subdivide beam-groups, providing the appropriate beam-breaks when sufficiently small durations are employed. \n",
    "\n",
    "The :meth:`beamSequence <music21.meter.TimeSignature.beamSequence>` MeterSequence is generally used to create and configure :class:`~music21.note.Beams` objects stored in :class:`~music21.note.Note` objects. The TimeSignature :meth:`~music21.meter.TimeSignature.getBeams` method, given a list of :class:`~music21.duration.Duration` objects, returns a list of :class:`~music21.note.Beams` objects based on the TimeSignature  :meth:`beamSequence <music21.meter.TimeSignature.beamSequence>` MeterSequence.\n",
    "\n",
    "Many users may find the Stream :meth:`~music21.stream.Stream.makeBeams` method the most convenient way to apply beams to a Measure or Stream of Note objects. This method returns a new Stream with created and configured Beams. \n",
    "\n",
    "The following example beams a bar of 3/4 in four different ways. The diversity and complexity of beaming is offered here to illustrate the flexibility of this model.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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fOzXMcmyY8/Nn51nn8Fn3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\nYQ3NS6UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 314,
       "width": 751
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts1 = meter.TimeSignature('3/4')\n",
    "ts1.beamSequence.partition(1)\n",
    "ts1.beamSequence[0] = ts1.beamSequence[0].subdivide(['3/8', '5/32', '4/32', '3/32'])\n",
    "\n",
    "ts2 = meter.TimeSignature('3/4')\n",
    "ts2.beamSequence.partition(3)\n",
    "\n",
    "ts3 = meter.TimeSignature('3/4')\n",
    "ts3.beamSequence.partition(3)\n",
    "\n",
    "for i in range(len(ts3.beamSequence)):\n",
    "    ts3.beamSequence[i] = ts3.beamSequence[i].subdivide(2)\n",
    "\n",
    "ts4 = meter.TimeSignature('3/4')\n",
    "ts4.beamSequence.partition(['3/8', '3/8'])\n",
    "for i in range(len(ts4.beamSequence)):\n",
    "    ts4.beamSequence[i] = ts4.beamSequence[i].subdivide(['6/32', '6/32'])\n",
    "    for j in range(len(ts4.beamSequence[i])):\n",
    "        ts4.beamSequence[i][j] = ts4.beamSequence[i][j].subdivide(2)\n",
    "\n",
    "s = stream.Stream()\n",
    "for ts in [ts1, ts2, ts3, ts4]:\n",
    "    m = stream.Measure()\n",
    "    m.timeSignature = ts\n",
    "    n = note.Note('b')\n",
    "    n.quarterLength = 0.125\n",
    "    m.repeatAppend(n, 24)\n",
    "    s.append(m.makeBeams())\n",
    "\n",
    "s.show()   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The following is a fractional grid representation of the four beam partitions created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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dqr6F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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# four beam partitions\n",
    "Image(filename='images/usersGuide/overviewMeters-03.jpg') #_DOCS_HIDE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Configuring Beat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The TimeSignature :meth:`beatSequence <music21.meter.TimeSignature.beatSequence>` MeterSequence employs the hierarchical structure to define the beats and beat divisions of a bar. The outer-most partitions can specify one or more top level beats. Inner partitions can specify the beat division partitions. For most common meters, beats and beat divisions are pre-configured by default.\n",
    "\n",
    "In the following example, a simple and a compound meter is created, and the default beat partitions are examined. The :meth:`~music21.meter.MeterSequence.getLevel` method can be used to show the beat and background beat partitions. The timeSignature :meth:`beatDuration <music21.meter.TimeSignature.beatDuration>`,  :meth:`beat <music21.meter.TimeSignature.beat>`, and :meth:`beatCountName <music21.meter.TimeSignature.beatCountName>` properties can be used to return commonly needed beat information. The TimeSignature :meth:`beatDivisionCount <music21.meter.TimeSignature.beatDivisionCount>`, and :meth:`beatDivisionCountName <music21.meter.TimeSignature.beatDivisionCountName>` properties can be used to return commonly needed beat division information. These descriptors can be combined to return a string representation of the TimeSignature classification with :meth:`classification <music21.meter.TimeSignature.classification>` property.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {1/4+1/4+1/4}>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts = meter.TimeSignature('3/4')\n",
    "ts.beatSequence.getLevel(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {1/8+1/8+1/8+1/8+1/8+1/8}>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatSequence.getLevel(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.duration.Duration 1.0>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatDuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatCount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Triple'"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatCountName"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatDivisionCount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Simple'"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatDivisionCountName"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Simple Triple'"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {3/16+3/16+3/16+3/16}>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts = meter.TimeSignature('12/16')\n",
    "ts.beatSequence.getLevel(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MeterSequence {1/16+1/16+1/16+1/16+1/16+1/16+1/16+1/16+1/16+1/16+1/16+1/16}>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatSequence.getLevel(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.duration.Duration 0.75>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatDuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatCount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Quadruple'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatCountName"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatDivisionCount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Compound'"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.beatDivisionCountName"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Compound Quadruple'"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Annotating Found Notes with Beat Count"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The :meth:`~music21.meter.TimeSignature.getBeat` method returns the currently active beat given a quarter length position into the TimeSignature.\n",
    "\n",
    "In the following example, all leading tones, or C#s, are collected into a new Stream and displayed with annotations for part, measure, and beat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wdfJ6GhsjNT7axfryWQtJTdrFUZVz/UmD4n6iKjAOVTXXJM95aUU/3PT+OuCf5RVHkibK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\nS8TVn0m+Mq/xZ5yrKJsStzZfgT1QpDzWuaoC41A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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 239,
       "width": 751
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from music21 import corpus\n",
    "score = corpus.parse('bach/bwv366.xml')\n",
    "ts = score.flat.getElementsByClass('TimeSignature')[0]\n",
    "ts.beatSequence.partition(3)\n",
    "\n",
    "found = stream.Stream()\n",
    "offsetQL = 0\n",
    "for part in score.parts:\n",
    "    found.insert(offsetQL, part.flat.getElementsByClass('Clef')[0])\n",
    "    for i in range(len(part.getElementsByClass('Measure'))):\n",
    "        m = part.getElementsByClass('Measure')[i]\n",
    "        for n in m.notesAndRests:\n",
    "            if n.name == 'C#':\n",
    "                n.addLyric('%s, m. %s' % (part.id[0], m.number))\n",
    "                n.addLyric('beat %s' % ts.getBeat(n.offset))\n",
    "                found.insert(offsetQL, n)\n",
    "                offsetQL += 4\n",
    "\n",
    "found.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Using Beat Depth to Provide Metrical Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Another application of the :meth:`beatSequence <music21.meter.TimeSignature.beatSequence>` MeterSequence is to define the hierarchical depth active for a given note found within the TimeSignature. \n",
    "\n",
    "The :meth:`~music21.meter.TimeSignature.getBeatDepth` method, when set with the optional parameter `align` to \"quantize\", shows the number of hierarchical levels that start at or before that point. This value is described by Lerdahl and Jackendoff as metrical analysis.\n",
    "\n",
    "In the following example, :meth:`beatSequence <music21.meter.TimeSignature.beatSequence>` MeterSequence is partitioned first into one subdivision, and then each subsequent subdivision into two, down to four layers of partitioning. \n",
    "\n",
    "The number of hierarchical levels, found with the :meth:`~music21.meter.TimeSignature.getBeatDepth` method, is appended to each note with the :meth:`~music21.note.GeneralNote.addLyric` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 595,
       "width": 751
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "score = corpus.parse('bach/bwv281.xml')\n",
    "partBass = score.getElementById('Bass')\n",
    "ts = partBass.flat.getElementsByClass('TimeSignature')[0]\n",
    "ts.beatSequence.partition(1)\n",
    "for h in range(len(ts.beatSequence)):\n",
    "    ts.beatSequence[h] = ts.beatSequence[h].subdivide(2)\n",
    "    for i in range(len(ts.beatSequence[h])):\n",
    "        ts.beatSequence[h][i] = ts.beatSequence[h][i].subdivide(2)\n",
    "        for j in range(len(ts.beatSequence[h][i])):\n",
    "            ts.beatSequence[h][i][j] = ts.beatSequence[h][i][j].subdivide(2)\n",
    "\n",
    "for m in partBass.getElementsByClass('Measure'):\n",
    "    for n in m.notesAndRests:\n",
    "        for i in range(ts.getBeatDepth(n.offset)):\n",
    "            n.addLyric('*')\n",
    "\n",
    "partBass.measures(0, 7).show()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Alternatively, this type of annotation can be applied to a Stream using the :func:`~music21.analysis.metrical.labelBeatDepth` function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Configuring Accent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The TimeSignature :meth:`accentSequence <music21.meter.TimeSignature.accentSequence>` MeterSequence defines one or more levels of hierarchical accent levels, where quantitative accent value is encoded in MeterTerminal or MeterSequence with a number assigned to the :meth:`weight <music21.meter.MeterTerminal.weight>` attribute.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Applying Articulations Based on Accent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The :meth:`~music21.meter.TimeSignature.getAccentWeight` method returns the currently active accent weight given a quarter length position into the TimeSignature. Combined with the :meth:`~music21.meter.TimeSignature.getBeatProgress` method, Notes that start on particular beat can be isolated and examined. \n",
    "\n",
    "The following example extracts the Bass line of a Bach chorale in 3/4 and, after repartitioning the beat and accent attributes, applies accents to reflect a meter of 6/8.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS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\nh4E1wHzgAeApLNAuIiIiIiIiBfL/7zQ/96QI+uEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 165,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "score = corpus.parse('bach/bwv366.xml')\n",
    "partBass = score.getElementById('Bass')\n",
    "ts = partBass.flat.getElementsByClass(meter.TimeSignature)[0]\n",
    "ts.beatSequence.partition(['3/8', '3/8'])\n",
    "ts.accentSequence.partition(['3/8', '3/8'])\n",
    "ts.setAccentWeight([1, .5])\n",
    "for m in partBass.getElementsByClass('Measure'):\n",
    "    lastBeat = None\n",
    "    for n in m.notesAndRests:\n",
    "        beat, progress = ts.getBeatProgress(n.offset)\n",
    "        if beat != lastBeat and progress == 0:\n",
    "            if n.tie != None and n.tie.type == 'stop':\n",
    "                continue\n",
    "            if ts.getAccentWeight(n.offset) == 1:\n",
    "                mark = articulations.StrongAccent()\n",
    "            elif ts.getAccentWeight(n.offset) == .5:\n",
    "                mark = articulations.Accent()\n",
    "            n.articulations.append(mark)\n",
    "            lastBeat = beat\n",
    "        m = m.sorted\n",
    "        \n",
    "partBass.measures(0, 8).show() "
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
